Enterprise Applications of Artificial Intelligence

Much of our conception of Artificial Intelligence or AI has been shaped by popular movies: from the homicidal Red Queen of “Resident Evil”, to the J.A.R.V.I.S. operating system / virtual butler that provides logistical support to “Iron Man”.

 

Extremely advanced intelligence and – in some cases – living machine consciousness.

 

We’re not quite there, yet (thankfully?). But there are real-world applications of AI that are already generating quite a buzz – and offering new tools and functionality that could prove beneficial to commercial enterprises and other institutions.

Some Intelligent Technologies

Artificial intelligence is the driving force within these technologies:

 

· Image Recognition: This technology uses image processing techniques (noise removal, etc.) to interpret groups of shapes in an image as specific single objects – even when viewed from different angles and lighting conditions.

 

· Pattern Recognition: The identification of relationships, objects, or types inferred from the observation of raw data.

 

· Speech Recognition: The use of algorithms and vocabulary databases to allow machines to correctly identify spoken words and phrases, and convert these into digital data that can be read as text (dictation software) or commands.

 

· Machine Learning: The objective of this technology is to develop computer applications that can adapt and evolve after exposure to new data – and “learn”, without being specifically programmed to do so.

 

· Deep Learning: Also known as deep machine learning or neural networking, this technology feeds natural language data into a computer, and repeatedly “quizzes” it on the information it has taken in, so that it can develop logical links between terms and phrases, and effectively “learn” to communicate in that language.

 

· Cognitive Computing: The creation of systems that “learn” through natural language processing, pattern recognition, and data mining. Cognitive computers imitate the way a human brain works, and are typically designed to easily interact with human users.

 

· Predictive Analytics: A data mining technique which, when applied to huge data sets (Big Data) can identify patterns, and predict future trends and outcomes.

AI at Work

Artificial Intelligence technologies are currently being used in a variety of industries, including:

 

· Healthcare

· The legal profession

· Online advertising

· Agriculture

· The automotive industry

· Manufacturing

· Oil and Gas industries

· The retail sector

· Banking and consumer finance

 

Research conducted by Tractica suggests that the enterprise market for AI applications will grow from a 2015 figure of $202.5 million to $11.1 billion by 2024.

How, not HAL

A 2015 survey by Tech Pro Research revealed that 63% of the organisations polled believed AI would be good for their business. But adoption rates were slow, with only 17% of those surveyed actively using AI.

 

This can partly be explained by a lack of trust in the technology – a problem exacerbated by the continued association of AI with killer computers like the HAL 9000 of “2001: A Space Odyssey”. People aren’t (yet) comfortable with the notion of a totally autonomous system.

 

Intelligent systems not only have to come up with solutions to industry-specific problems – they have to be transparent in the way these solutions are presented. Humans using AI technology expect their hardware and software to explain how results were obtained.

Cognitive Computing, in Action

When used as a tool, a learning computer should be a complement to the intelligence of its users, augmenting their skills with the computational power and data handling skills that humans naturally lack.

 

Rather than displacing workers and losing jobs, a cognitive system and its related applications should assist and enhance, using AI technology to “humanise” the interface between person and machine.

 

A case in point is the Chef Watson application developed by IBM. Drawing from an extensive database of human culinary preferences and the chemical composition of various ingredients, the program is able to create fresh and unpredictable combinations of foods that nonetheless make for appetising meals.

Advances in Law and Medicine

On a more serious note, AI has already found a niche in the legal and medical sectors.

 

Cognitive Scale has developed a mobile App which acts as an assistant / concierge for patients at the MD Anderson Cancer Centre in Houston, Texas. The app can make recommendations for example on best dietary choices, based on a patient’s medical history, recent changes in medication, and individual preferences.

 

In both the medical and legal professions, practitioners need to make constant reference to a vast body of empirical, anecdotal, research and other knowledge – data which is constantly being updated as fresh cases are judged, new discoveries are made, and publications are released online.

 

With its computational powers and ability to digest and interpret vast amounts of information, AI technology is uniquely placed to play a role in making these resources available to legal and medical practitioners, on demand.

Investing in the Future

The commercial possibilities of AI haven’t escaped the big players.

 

Besides IBM, Google has recently invested in some 30 companies – four of which have an AI focus. Cognitive Scale was founded by a former IBM researcher who was part of the Watson project. And Microsoft’s Project Adam is looking to integrate AI with mainstream Windows products.

Beyond Cortana

The ultimate success (or otherwise) of AI technology will lie in its ability to create human-computer interfaces that serve their stated functions, and which people actually want to buy and use.

 

With Artificial Intelligence, the age of the thinking virtual assistant – able to help us co-ordinate our working and personal lives, manage projects, perhaps be wearable – is almost upon us.

 

And businesses will require intelligent tools to make sense of all the data coming in from AI devices worn by their employees, attached to corporate assets, and helping to regulate their operations.